mlpack IRC logs, 2020-03-30

Logs for the day 2020-03-30 (starts at 0:00 UTC) are shown below.

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--- Log opened Mon Mar 30 00:00:50 2020
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06:15 < Saksham[m]> zoq In the proposal would you prefer a week by week timeline or we can do it by phases and later break it down during the bonding period ?
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07:52 < bisakh[m]1> Saksham: I am not sure, though the application guide says it better to have week by week plan. "*Describe a timeline of some sort for your project, broken down week by week (or thereabouts)."*
07:54 < bisakh[m]1> Hey zoq I had something in my mind, so asked you on DM. If time permits, please respond
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10:41 < mtnshhGitter[m]> Hey Everyone, I am Miten Shah. I have submitted my draft in GSoC website. Any suggestions and reviews are most welcome.
10:41 < mtnshhGitter[m]> Thank you, in advance.
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11:34 < PrinceGuptaGitte> Hello @zoq, when we want to train a convnet from a dataset it will be a good idea to have a `ImageDataGenerator` of MLPack like keras have so training a convnet will become less complicated for end MLPack users.
11:36 < PrinceGuptaGitte> My gsoc idea also requires training a convnet, so should I add this to my objectives in coding periodor should I start working on it pre gsoc(which I think will be better incase other projects also require training convnet)
12:06 < zoq> PrinceGuptaGitte: If you like you can add this one to your timeline, if I remember right kartikdutt18Gitt is working on something like this already.
12:07 < Saksham[m]> Hey zoq should the schedule be Broken down week by week ?
12:08 < zoq> Saksham[m]: Saksham[m]: Ideally, you can already break it down before the community bonding time, but we can certainly use the bonding time for refinement.
12:09 < Saksham[m]> zoq Okay thanks, I’ve done it in phases currently
12:09 < kartikdutt18Gitt> Hey zoq, prince776, I am working on a data loader for models repo. I think it's more suited there, I have already added support to load images / data from CSV files. It will be extended to support images as well. Prince if you feel there is something missing there after it's merged you can always open a PR for the same.
12:11 < kartikdutt18Gitt> Hey zoq, Could you help me out with a question, I am trying to run LSTM example on Jupyter notebook, However ensmallen stops after one epoch, any idea why that might happen?
12:11 < zoq> kartikdutt18Gitt: And I guess the plan is to have a method to load specific datasets as well, like mnist?
12:11 < kartikdutt18Gitt> The notebook can be found [here](https://github.com/kartikdutt18/examples/blob/Add-example-notebooks/lstm_stock_prediction/LSTM_MULTIVARIATE_TIME_SERIES.ipynb).
12:12 < kartikdutt18Gitt> Yes, I have already added support for mnist and next one on the list is PASCAL dataset.
12:13 < kartikdutt18Gitt> A user could just pass Dataloader("mnist", train_test_split = 0.9, other_params_if_any);
12:14 < zoq> kartikdutt18Gitt: Not sure yet, have to take a closer look, btw. I have a jupyterhub setup that makes the first part obsolete, and uses a more recent cling version; will open a PR with an example later as well.
12:15 < zoq> kartikdutt18Gitt: Not sure yet, we should include a bunch of extra information.
12:17 -!- M_slack_mlpack_7 is now known as DivyanshKumar[m]
12:17 < DivyanshKumar[m]> Hello everyone 👋👋👋 I have a doubt that how to do good testing
12:20 < zoq> DivyanshKumar[m]: Not sure I can provide a good answer, it's challenging and often harder as writing the implementation itself. And of course depends on the method/topic.
12:21 < kartikdutt18Gitt> Ohk great, thanks a lot. I'll try adding more information and fixing it till then.
12:22 < GauravTirodkar[m> Anyone applying for the reinforcement learning project?
12:23 < AbishaiEbenezerG> yes, i did...
12:23 < DivyanshKumar[m]> Gaurav Tirodkar I have also applied for it
12:23 < GauravTirodkar[m> which algos are you guys applying ?
12:24 < DivyanshKumar[m]> I am using rainbow with NEAT
12:24 < DivyanshKumar[m]> What about you
12:25 < GauravTirodkar[m> I am looking at the Double Q-learning
12:25 < PrinceGuptaGitte> @kartikdutt18 I have looked at the dataloader you worked on in the restructuring, I had one doubt about the implementation, you have added data loader function for each different dataset. By ImageDataGenerator I meant a general utility function/class that can be used to automatically load images from directories while being labeled, just like keras does it, so it can be used on any dataset, since most of image
12:25 < PrinceGuptaGitte> datasets are available in this format where subdirectories have name of class they belong to.
12:27 < DivyanshKumar[m]> Gaurav Tirodkar nice so how you are going to test your algo
12:27 < PrinceGuptaGitte> I haven't seen your implementation of image loaders yet so I can be wrong.
12:28 < PrinceGuptaGitte> Also this way we can have features like augmentation, while loading.
12:28 < GauravTirodkar[m> What about you Divyansh Kumar?
12:29 < GauravTirodkar[m> What about you Divyansh Kumar?
12:29 < GauravTirodkar[m> I thought of training a Mario game to complete a track? What are your thoughts?
12:30 < PrinceGuptaGitte> I think I will add this feature as "if required" in the timeline, is that a good idea @zoq ?
12:30 < bisakh[m]1> Prince Gupta: That's a good idea, The same thing is done by PyTorch using ImageFolder
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12:32 < PrinceGuptaGitte> Thanks vikash
12:32 < zoq> PrinceGuptaGitte: Sure why not.
12:32 < PrinceGuptaGitte> Bikash*
12:32 < DivyanshKumar[m]> Gaurav Tirodkar I think about mario or some other game like that
12:33 < Saksham[m]> Gaurav Tirodkar its already implemented
12:33 < Saksham[m]> Double q learning
12:33 < DivyanshKumar[m]> I will work using pixel mechanism
12:33 < PrinceGuptaGitte> Thanks zoq
12:35 < DivyanshKumar[m]> I have a doubt that timeline should be extended showing every movement in project or just basic..
12:38 < zoq> DivyanshKumar[m]: Add details you think are important.
12:39 < kartikdutt18Gitt> @prince776, The dataloader that I am implementing is generic i.e. When I am done extending it for images it will be able to load images from directory and csv (different from csv with images in it). One thing I want to maintain in models repo is that users should be able to write simpler code and having generic function helps that.
12:40 < kartikdutt18Gitt> For augmentation, that will be added as seen from the current dataloader.
12:41 < PrinceGuptaGitte> Oh that's great.
12:46 < kartikdutt18Gitt> And one last thing, we won't have separate function for each dataset that will add to redundancy in codebase, we will have three functions, one for CSV, one for directory and one for one other for csv that has image paths. For popular datasets all values required by them will be set rather than having hard coded data loader. You can refer to how the mnist is called. If you have any questions or suggestions, let me
12:46 < kartikdutt18Gitt> know I'll try to incorporate them. More such functions can be added when they are required. As I said before you can always open a PR to add them.
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12:58 < AbishaiEbenezerG> hey @zoq, for gsoc i proposed multi agent RL, where we could use a multi actor critic model (multi agent deep DPG). I also proposed to create a few relevant environments and policies.
12:58 < AbishaiEbenezerG> Maybe you have some thoughts....
13:00 < AbishaiEbenezerG> Any other mentor's inputs would be great as well
13:06 < GauravTirodkar[m> <Saksham[m] "Gaurav Tirodkar its already impl"> using mlpack? What I saw was python based
13:08 < Saksham[m]> <GauravTirodkar[m "using mlpack? What I saw was pyt"> Yes using mlpack, it’s the same file as q learning and can be used after passing a parameter
13:13 < GauravTirodkar[m> <Saksham[m] "Yes using mlpack, it’s the same "> Can you send me the link??
13:13 < GauravTirodkar[m> <GauravTirodkar[m "Can you send me the link??"> They have included Double QLearning in the project idea
13:14 < Saksham[m]> <GauravTirodkar[m "They have included Double QLearn"> <https://github.com/mlpack/mlpack/tree/master/src/mlpack/methods/reinforcement_learning>
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13:18 < y2s> Hello everyone. I submitted a GSoC proposal on converting more code into parallelization using OpenMP. I would appreciate if any mentor would take a look at make some suggestions :)
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13:24 < GauravTirodkar[m> <Saksham[m] "<https://github.com/mlpack/mlpac"> Thanks
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13:48 < JoelJosephGitter> i can see LogSoftMax in the docs, but not regular SoftMax. Is the syntax: "model.Add<SoftMax<>>();"
13:49 < kartikdutt18Gitt> Hi Joel, There is a PR open for softmax (as far as I can remember) but I don't think it's already present in mlpack.
13:59 < JoelJosephGitter> ohk
14:00 < JoelJosephGitter> :)
14:40 < JoelJosephGitter> is there a layer which can keep its output finite, like "between 0 and 1" or "-1 and +1" that is currently implemented in mlpack
14:45 < kartikdutt18Gitt> I think you could use sigmoid function or maybe some other activation function. Let me know what you think.
14:46 < JoelJosephGitter> whats the syntax for adding sigmoid
14:48 < kartikdutt18Gitt> model.Add<SigmoidLayer<>>();
14:49 < JoelJosephGitter> ill try that, thanks :)
14:49 < kartikdutt18Gitt> In general, you can refer to base_layer.hpp for more details on how activation functions are used as layers. Some activation_functions are also implemented as layer.
15:04 < GauravTirodkar[m> I was trying for Reinforcement Learning by using Double Q-Learning algo. But it seems like it is already implemented here(<https://github.com/mlpack/mlpack/tree/master/src/mlpack/methods/reinforcement_learning>). Can someone guide me with this ?
15:05 < SriramSKGitter[m> @gaurav_tirodkar : Yes, Double Q Learning is already implemented in mlpack. What did you want to know?
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15:14 < SriramSKGitter[m> Rainbow DQN is indeed included in the projects list, but it is a combination of 6 extensions to the standard DQN, of which Double Q Learning is one. So while, Double Q Learning and a couple other components of the RainbowDQN are already implemented, there are a few which are not. https://arxiv.org/abs/1710.02298
15:14 < SriramSKGitter[m> Hope I was helpful :)
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15:21 < GauravTirodkar[m> Yes. Thanks A Lot !
15:21 < SriramSKGitter[m> Anytime :)
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15:37 < DivyanshKumar[m]> I am using noisy nets method with gamma function will it be ok
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16:59 < GauravTirodkar[m> Has Duel DQN being implemented ?
17:00 < Saksham[m]> <GauravTirodkar[m "Has Duel DQN being implemented ?"> No not yet
17:03 < GauravTirodkar[m> <Saksham[m] "No not yet"> OH Great
17:03 < GauravTirodkar[m> <GauravTirodkar[m "OH Great"> Thanks
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18:10 < LakshyaOjhaGitte> Hey @sreenik I have done some updates in the same proposal hope you get time to review the same. :)
18:10 < LakshyaOjhaGitte> Gn
18:29 < sreenik[m]> ojhalakshya[m]: Sure, I'll do it now
18:48 < GauravTirodkar[m> I've completed my proposal, how can I get it reviewed ?
19:00 < AnjishnuGitter[m> Hi! @zoq @sreenik I have uploaded a draft proposal. Could you have a look at it if you get some time? Thanks!
19:04 < GauravTirodkar[m> Hello !! I have completed and uploaded the draft on GSoC. Please verify it as time permits. Thanks in advance !!
19:08 < naruarjun[m]> Hello, I had submitted a draft on 22nd March. It would be really appreciated if any of the mentors could review it. Especially @zoq or Manish Kumar as they are listed as potential mentors for the RL project.
19:12 < zoq> naruarjun[m]: What's the title of the application, pretty sure I checked the RL applications at that point.
19:13 < naruarjun[m]> <zoq "naruarjun: What's the title of t"> Implementation A2C, PPO and TRPO for mlpack
19:13 < sreenik[m]> iamshnoo[m]: Sure. I actually scrolled through it but I guess I'll take some time to review it. I hope it's not an issue :)
19:16 < AnjishnuGitter[m> Sure! Its a bit lengthy. Thanks for just scrolling through it even :)
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19:16 < zoq> naruarjun[m]: Ahh, I can't comment on the draft.
19:16 < naruarjun[m]> * > <@freenode_zoq:matrix.org> naruarjun: What's the title of the application, pretty sure I checked the RL applications at that point.
19:16 < naruarjun[m]> Implementation of A2C, PPO and TRPO for mlpack
19:17 < sreenik[m]> iamshnoo[m]: haha
19:18 < naruarjun[m]> <zoq "naruarjun: Ahh, I can't comment "> Oh, why is that? Is it some setting issue from my side?
19:18 < zoq> naruarjun[m]: Yes, nothing I can do.
19:19 < sreenik[m]> naruarjun: It's probably because you haven't given proper permissions to the google doc
19:21 < naruarjun[m]> I have changed it
19:22 < zoq> naruarjun[m]: Don't think the default setting allows anyone to comment on the doc.
19:22 < naruarjun[m]> Sorry I didn’t know I had to change the can view to can edit as well. Hope you can review it.
19:24 < zoq> naruarjun[m]: No worries, we can always mail people after the deadline and ask for clarification, if there is something that needs clarification.
19:25 < abhisaphire[m]> Hey zoq zoq
19:25 < abhisaphire[m]> If you have time, please re-visit my proposal too and check if i have made correct adjustments according to your comment oe not. (Name - Abhishek kumar Singh)
19:25 < abhisaphire[m]> Proposal on automatic binding generator for Octave
19:27 < naruarjun[m]> <zoq "naruarjun: No worries, we can al"> Ok. Thanks for the help.
19:38 < zoq> abhisaphire[m]: Don't think I can re-visit a proposal, if you addressed the comments it's fine, we can aks for clarification after the deadline, so no worries.
19:51 < Param-29Gitter[m> Hey @zoq, if you have time please have a look on my proposal too .
19:51 < zoq> Param-29Gitter[m: What's the title?
19:53 < Param-29Gitter[m> Profiling for parallelism
19:53 < zoq> Hm, I think I looked into that application, maybe not.
19:54 < Saksham[m]> Hi zoq I submitted my proposal 4-5 days ago, please have a look when you get time
19:54 < Saksham[m]> It’s on Enhance CMA-ES
19:54 < Param-29Gitter[m> I checked the settings, they are fine.
19:59 < GauravSinghGitte> Hi, @zoq if you get a chance kindly review my proposal also. Applied for 'Enhance CMA-ES'. Thank you.
20:00 < zoq> GauravSinghGitte: Done, like some minutes ago.
20:05 < GauravSinghGitte> Thank you very much @zoq for the review and regarding the link you asked for the project I haven't uploaded iton github yet. Will email you the link once I do it. Thanks.
20:06 < GauravSinghGitte> (edited) ... uploaded iton github ... => ... uploaded it on github ...
20:07 < zoq> GauravSinghGitte: Ahh okay, thanks, I will definitely apply the cf code and see how far we are from the winning solution.
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21:36 < y2s> wow, zoq[m], may I also ask you to review my proposal? It's on profiling for parallization
21:44 < zoq> y2s: Hm, not sure I can see the application, what name did you use?
21:52 < y2s> zoq[m]: my name is Tony Sim, and my google id is y2s1982. Hope that helps
21:53 < zoq> y2s: Via the GSoC dashboard?
21:53 < y2s> yes
21:54 < zoq> y2s: "Profile-driven parallelization using OpenMP"?
21:54 < y2s> that's me :)
21:55 < zoq> y2s: I see, that is already marked as final, I can comment on the draft but I don't think you can submit a change.
21:56 < y2s> oh, I can. It told me to resubmit as much as I wish. I already resubmitted a few times, too
21:56 < zoq> y2s: ahh nice
21:57 < y2s> zoq, I really appreciate it.
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--- Log closed Tue Mar 31 00:00:52 2020